Distribution of PCDD/Fs and PCBs in soil and pine needles in Ulsan, South Korea. For data interpretation, spatial distributions, compositions and correlations of PCDD/Fs and PCBs in soil and pine needles were performed.
INTRODUCTION
PCBs also have similar pathways to PCDD/Fs, which will contaminate the environment, disrupting the food chain system (Nieuwoudt et al., 2009). Among studies in South Korea, levels of persistent organic pollutants in animal and plant products, including human risk assessments, were observed and evaluated through dietary intake and skin contact (Chung et al., 2018).
MATERIALS AND METHODS
- Sampling methods
- Pretreatment procedures
- Instrumental analysis
- Quality assurance and quality control
- Lipid content and TOC
- Lipid content in pine needles
- Total organic carbon content in soils
- Statistical analysis
Media lipid content was measured to correlate organic pollutant levels with lipid content in each sample. Lipid content was calculated by subtracting the weight of the flask after and before extraction.
RESULTS AND DISCUSSION
Distribution of PCDD/Fs in soils and pine needles
- Total concentrations of PCDD/Fs
- Spatial distribution of PCDD/Fs
- Average and individual profiles of PCDD/Fs
- Principal component analysis of PCDD/Fs
In Figure 9a, most industrial sites show higher concentrations of PCDD/Fs in soil than those of other areas, and this result is consistent with those of previous studies (Dömötörová et al., 2012; Nieuwoudt et al., 2009; Wu et al. ., 2018), but some suburban sites (S9 to 12) had similar PCDD/F levels to industrial sites, meaning those sites may have been contaminated by local sources such as agricultural wood fires or traffic events (Schuhmacher et al. , 2004). Similar trends were found in previous studies in China and Spain (Schuhmacher et al., 2004; Zhang et al., 2009). This result can mainly be attributed to incomplete combustion, as the ratio of ∑10PCDFs to ∑7PCDDs is greater than unity (Chen et al., 2012).
The purpose of PCA is to characterize pollution patterns from different industrial and other sources (regional or local) from the sampling sites (Cho et al., 2019). In particular, higher chlorinated dioxins such as OCDDs can be formed through natural processes such as biomass burning, and therefore, most peripheral sites had high fractions of OCDDs (Breivik et al., 2004). It is assumed that urban areas are mainly affected by industrial processes through long-range transport, which may play an important role in environmental levels of these pollutants (Schuhmacher et al., 2004).
In this case, they were possibly contaminated by the historical use of pesticides for agricultural activities or by illegal burning (Bochentin et al., 2007). The previous studies reported that pesticide products containing pentachlorophenol (PCP) for agricultural activities have been banned in South Korea since the 1970s, and therefore their influence on high fractions of OCDDs is less likely (Masunaga et al., 2001).
Distribution of dl-PCBs in soils and pine needles
- Total concentrations of dl-PCBs
- Spatial distribution of dl-PCBs
- Average and individual profiles of dl-PCBs
- Principal component analysis of dl-PCBs
In general, industrial areas showed higher concentrations of dl-PCBs in soil than those from suburban and urban areas. The stacked bar graphs of dl-PCB congeners in concentrations at all sites are shown in Figure 16. In Figure 16a, some industrial sites showed higher concentrations of dl-PCBs in soil than those in other areas, which is comparable to that of PCDD/Fs in soils.
Of the sampling sites, soil in the suburban site (S11) had the highest concentration of dl-PCBs similar to that of industrial sites. In Figure 16b, the patterns of dl-PCBs in pine needles at sampling sites were similar, except for one industrial area (I3) with a higher concentration of dl-PCBs, assuming that thermal processes from the non-ferrous industries took place (Antunes ) et al., 2012). In Figure 17b, the distribution patterns of dl-PCB congener groups in pine needles were the same as those of soils.
PCA scores and loading plots for dl-PCBs in soil from the sampling sites are shown in Figure 19. PCA scores and loading plots for dl-PCBs in pine needles from the sampling sites are shown in Figure 20.
Distribution of indicator PCBs in soils and pine needles
- Total concentrations of indicator PCBs
- Spatial distribution of indicator PCBs
- Average and individual profiles of indicator PCBs
- Principal component analysis of indicator PCBs
In general, higher concentrations of indicator PCBs were found in soil in industrial areas than in suburban and urban areas. The stacked bar graphs of indicator PCB congeners in concentrations at all sites are shown in Figure 23. In Figure 23a, most industrial sites showed higher concentrations of indicator PCBs in soil than those in other areas, and this result is consistent with that from the previous study. study conducted at the same site, Ulsan, and I8 had the highest concentration of indicator PCBs among the sampling locations due to its influence on automotive activities (Nguyen et al., 2016).
In Figure 23b, the patterns of indicator PCBs in pine needles among the sampling sites are not shown. PCA scores and loading plots for indicator PCBs in soil and pine needles from the sampling sites are shown in Figure 26 and Figure 27, including the commercial products called Aroclor 1254 and 1260 as input data for the PCA to compare the contamination profiles of each medium and to identify the potential PCB emission sources based on PCA results (Frame et al., 1996; Nguyen et al., 2016). PCA scores and loading plots for indicator PCBs in soil from the sampling sites are shown in Figure 26, and PC 1 and PC 2 accounted for 64% and 26% of the total variance.
The PCA result and loading curves for the indicator PCBs in pine needles from the sampling sites are shown in Figure 27, with PC 1 and PC 2 accounting for 62% and 31% of the total variance. The pine needle sample from I7, as mentioned earlier, had a similar trend to indicator PCBs in soil.
Global comparisons of target compounds
- Comparisons of PCDD/F concentrations
- Comparisons of PCB concentrations
Global comparisons of PCDD/F concentrations in soil and pine needles between this study and other studies (median values are in bold). The measured levels of 18 PCBs in soil and pine needles between this study and previous studies are listed in Table 7. In comparing TEQ concentrations in this study, they were much lower than those in other studies, except 0 .29 and 0.007 pg- TEQ/g dw from e-waste dismantling and recycling sites in China (Liu et al., 2020).
Although e-waste disposal was the main source of dl-PCBs, relatively low TEQ concentrations were shown in this table in Liu's study. When comparing the pine needle results with those from the previous studies, both the average PCB levels and total PCB concentration ranges at all sampling areas in this study were lower than those in previous studies, except 110−420 pg/g ww of the locations near Tokyo Bay, Japan (Hanari et al., 2004). In the case of pine needle TEQ concentrations, all other sites except sites near Tokyo Bay (Hanari et al., 2004) and sites in Europe (Holt et al., 2016) showed moderate and lower total TEQ concentrations compared to the results of this study.
Global comparisons of PCB concentrations in soils and pine needles between this study and other studies (average values are in bold).
Spearman correlation results
- Correlations between PCDD/Fs, TOC, and lipid content
- Correlations between PCBs, TOC, and lipid content
- Correlations between PCDD/Fs, PCBs, and organic contents
Spearman correlations between PCDD/Fs, ∑17PCDD/Fs, ∑7PCDDs, ∑10PCDFs and lipid content (%) in pine needles. Correlations between PCBs, ∑18PCB and TOC in soil were determined by Spearman correlation analysis (Table 10). Correlations between PCBs, ∑18PCBs and lipid content in pine needles were examined by Spearman correlation analysis (Table 11).
Based on this result, the lipid content was negatively correlated with some congeners (PCB 118, PCB 123, PCB 138) and ∑18PCBs. The Spearman correlations between the sum of PCDD/Fs, dl-PCBs, indicator PCBs (I-PCBs) and TOC in soil were determined by Spearman correlation analysis (Table 12). Spearman correlations between the sum of PCDD/Fs, dl-PCBs and indicator PCBs and TOC (%) in soil.
Correlations between the sum of PCDD/Fs, dl-PCBs, indicator PCBs and lipid content in pine needles are shown in Table 13. Spearman correlations between the sum of PCDD/Fs, dl-PCB 's and indicator PCBs and lipid content (%) in pine needles.
Physicochemical properties of PCDD/Fs and PCBs in media
- Comparisons of PCDD/Fs between two media
- Comparisons of PCBs between two media
The PCA was performed to see the relationship between 18 PCB congeners and samples at sampling locations shown in Figure 29. The PC 1 and PC 2 for the sampling locations accounted for 43% and 24% of the total variance, respectively. Similar to the PCA results of PCDD/Fs, the soil and pine needle samples at each site were clearly separated based on their congener profiles previously reported in Figures 18 and 25.
The soil samples were somewhat scattered in the results plot with positive PC 1 loadings of highly chlorinated PCBs (penta- to hepta-CB). PCB homologues larger than penta-CB have higher Koa, which are easily deposited on soil, water surface and plants with less volatilization, leading to continuous deposition (Yeo et al., 2004). Pine needle samples from all sites were collected on the left side of the results plot with negative PC 1 loadings of lower chlorinated PCBs (tri- to tetra-CB).
This phenomenon has been well reported in the previous studies that the congeners in the gas phase tend to penetrate via stomata of the pine needles due to the low Kow, while higher chlorinated (penta-to-hexa-) PCBs bound to particles are likely to be adsorbed to the epicuticular wax surface for a short period of time (Baráková et al., 2017; Chen et al., 2006; Liu et al., 2020).
CONCLUSIONS
Estimation of PCDD/Fs concentrations in ambient air using pine needles as a passive air sampler (PAS). Concentration measurements of PCDD/F in air and spruce needles in the Bavarian Forest and the Bohemian Forest (Sumava): first results. Severe contamination of PCDD/Fs and dioxin-like PCBs in sediments of Lake Shihwa, Korea: tracing the source.
Atmospheric concentrations of PCDD/Fs, dl-PCBs and some pesticides in northern Algeria using passive air sampling. Characterization of PCDD/Fs and dioxin-like PCBs in flue gas from thermal industrial processes in Vietnam: a comprehensive study of emission profiles and levels. Levels of PCDD/Fs, PCBs and PCNs in soils and vegetation in an area with chemical and petrochemical industries.
PCDD/Fs pollution characteristics and source relationships in industrial complexes in Korea. Source identification of PCDD/F and PCBs in pine needles (Cedrus deodara): a case study in Dalian, China.
